In the ever-evolving field of agritech, innovation isn’t just about introducing new tools—it’s about reshaping traditional practices through cutting-edge technology. When an agronomist approached Roughly with the idea of using AI to increase efficiency in his operations, we saw a fantastic opportunity to explore how artificial intelligence could transform his work. Our goal was clear: to design an AI-powered solution that would optimize workflows and increase productivity, all while keeping the human element front and center.

For this post, we have to keep things somewhat high level and the client anonymous, as the project is still in a discovery stage. But given the work done. we felt it was worth getting into approach of project discovery and idea validation.

Product Discovery: Understanding Workflows from All Angles

In any project, the key to success is a deep understanding of the people who will be using the technology. During the Product Discovery phase, we dug into the day-to-day tasks not just of the agronomist, but also the farmers working alongside him. We applied our human-centered design approach to map out how both parties interact with the existing processes and explored how AI could help streamline their operations without disrupting their workflows.

By focusing on the needs, behaviors, and challenges of the people using the system, we were able to design a platform that felt intuitive and addressed their pain points. For the agronomist, it was all about quick, data-driven decision-making; for the farmers, it was about ease of use and reliability in the field.

Prototyping and Roadmap Development: Building Solutions that Work for Everyone

Once we understood the workflows of both the agronomist and the farmers, we moved into the Prototyping phase. We created early versions of AI-driven tools that would become part of their routine, ensuring that these solutions not only delivered efficiency but also aligned with how they preferred to work. The focus was always on making the technology seamless and practical for users at every level.

In parallel, we developed a detailed Roadmap, ensuring the project had a clear path from concept to deployment. The roadmap took into account future scalability, so as the agronomist’s operations grew, the AI solution could grow with him, accommodating more data and more users without any hitches.

Human-Centered AI for Precision Agriculture

Precision agriculture demands accuracy, and AI is the perfect tool to achieve this. By applying Product Design principles that focused on usability, we created a platform that didn’t just analyze data but did so in a way that was easy for the agronomist to act upon. Whether it was soil analysis, crop health monitoring, or yield predictions, the AI solution was designed to fit seamlessly into existing workflows.

Our commitment to human-centered design ensured that the platform was more than just functional—it was an empowering tool that made both the agronomist’s and the farmers’ lives easier. The result? A smarter, more efficient operation that didn’t compromise on user experience while ensuring that farmers could get a new tool that allows them to make data driven decisions along the way.

In this process we also had to ask ourselves, is this new wave of AI through the explosion of Large Language Models(LLMs) going to kickstart the conversation of whether AI is a product or a feature?

At roughly, we feel AI models will most likely become a product, where as most AI functionality will become features living within applications.